ScienceDirect
Available online at
Available online at www.sciencedirect.com
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ScienceDirect
Energy Procedia 00 (2017) 000–000
www.elsevier.com/locate/procedia
1876-6102 © 2017 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.
The 15th International Symposium on District Heating and Cooling
Assessing the feasibility of using the heat demand-outdoor
temperature function for a long-term district heat demand forecast
I. Andrić
a,b,c*, A. Pina
a, P. Ferrão
a, J. Fournier
b., B. Lacarrière
c, O. Le Corre
c aIN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, PortugalbVeolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France
cDépartement Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France
Abstract
District heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the
greenhouse gas emissions from the building sector. These systems require high investments which are returned through the heat
sales. Due to the changed climate conditions and building renovation policies, heat demand in the future could decrease,
prolonging the investment return period.
The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand
forecast. The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665
buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district
renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were
compared with results from a dynamic heat demand model, previously developed and validated by the authors.
The results showed that when only weather change is considered, the margin of error could be acceptable for some applications
(the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation
scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered).
The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the
decrease in the number of heating hours of 22-139h during the heating season (depending on the combination of weather and
renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the
coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and
improve the accuracy of heat demand estimations.
© 2017 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and
Cooling.
Keywords: Heat demand; Forecast; Climate change
Energy Procedia 157 (2019) 180–192
1876-6102 © 2019 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
10.1016/j.egypro.2018.11.179
Available online at www.sciencedirect.com
ScienceDirect
Energy Procedia 00 (2018) 000–000
www.elsevier.com/locate/procedia
1876-6102 © 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,
19–21 September 2018, Athens, Greece
Economic parameters in the evaluation studies focusing on
building energy efficiency: a review of the underlying
rationale, data sources, and assumptions
Sergio Copiello
a*
aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy
Abstract
A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the
economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a
literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the
energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,
namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and
abstracts of the examined documents. The representation of the results allows recognizing several significant clusters
and network relationships. Moreover, that literature review enables to identify two well-established research strands.
The first involves the relationship between energy prices and the profitability of efficiency-related investments. The
second research branch points at the pivotal role played by the discount rate when evaluating the investments in
energy-efficient measures.
© 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (
https://creativecommons.org/licenses/by-nc-nd/4.0/
)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,
Environment and Sustainability, TMREES18.
Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate
* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it
10.1016/j.egypro.2018.11.179
© 2019 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (
https://creativecommons.org/licenses/by-nc-nd/4.0/
)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,
Environment and Sustainability, TMREES18.
1876-6102
ScienceDirect
Energy Procedia 00 (2018) 000–000
www.elsevier.com/locate/procedia
1876-6102 © 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,
19–21 September 2018, Athens, Greece
Economic parameters in the evaluation studies focusing on
building energy efficiency: a review of the underlying
rationale, data sources, and assumptions
Sergio Copiello
a*
aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy
Abstract
A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the
economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a
literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the
energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,
namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and
abstracts of the examined documents. The representation of the results allows recognizing several significant clusters
and network relationships. Moreover, that literature review enables to identify two well-established research strands.
The first involves the relationship between energy prices and the profitability of efficiency-related investments. The
second research branch points at the pivotal role played by the discount rate when evaluating the investments in
energy-efficient measures.
© 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (
https://creativecommons.org/licenses/by-nc-nd/4.0/
)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,
Environment and Sustainability, TMREES18.
Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate
* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it
2 Sergio Copiello / Energy Procedia 00 (2018) 000–000
1. Introduction
The issue of building energy efficiency has gained interest during the last years and, more broadly, over a time
span of four decades or so [
1] (Fig. 1
). Energy efficiency is a prominent topic on the agenda due to the need of taking
fuel consumptions under control and reducing their environmental impact. Under this framework, the construction
sector plays a pivotal role because buildings largely contribute to primary energy demand and consumption, as well
as to greenhouse gas emissions [
2-4]. Concerning the evaluation of the measures aiming at improving building energy
efficiency, a growing literature is available. The results of several field studies, although sometimes conflicting, have
the merit of having highlighted the variables and parameters that most affect the technical feasibility and the economic
viability of those measures. As far as the latter is concerned, a summary list of the most influential parameters should
include, at least, the following items [
1,5]: contingent and long-term geo-climatic conditions [6,7]; building type and
physical characteristics of the constructions [
8,9]; consumers’ preferences and occupants’ behavior [10-13]; prices of
energy supply and their changes over time [
14-16]; investment costs to be incurred and the corresponding expected
return and payback time [
17-19].
Fig. 1. Growing interest for building energy efficiency (source: Google Ngram Viewer).
This paper aims to present the results of a systematic literature review, with regard to the studies that use economic
parameters to assess the feasibility of energy efficiency measure in the building industry. The literature review
purposely focuses on the following three economic parameters: the price to be paid for the energy supply; the inflation
rate, especially as far as energy sources are concerned; the discount rate used to convert future values to present values,
so to calculate the upfront lump-sum equivalent of the expected cash flows.
The structure of this paper is as follows. The next section describes the source used to gather information and the
method followed to identify the relevant literature. The subsequent paragraph provides an overview of the results,
with specific reference to these issues: topics addressed in the studies, data sources, and estimated values or
assumptions as far as the economic parameters are concerned. A further part of the text is devoted to identify and
discuss two main, well-established research strands: the role played by energy prices in techno-economic evaluations
is the former, the prominence of the discount rate in the same evaluations is the latter. Finally, the last section draws
the conclusions.
2. Method
The literature review discussed in this study is based on bibliographic research, which has been performed using
the indexing and abstracting database Scopus, provided by Elsevier. Although some limitations and other issues are
known to affect the selected source [
20-23], it has been chosen due to its wider coverage in comparison to others such
Sergio Copiello / Energy Procedia 157 (2019) 180–192 181
Available online at www.sciencedirect.com
ScienceDirect
Energy Procedia 00 (2018) 000–000
www.elsevier.com/locate/procedia
1876-6102 © 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,
19–21 September 2018, Athens, Greece
Economic parameters in the evaluation studies focusing on
building energy efficiency: a review of the underlying
rationale, data sources, and assumptions
Sergio Copiello
a*
aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy
Abstract
A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the
economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a
literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the
energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,
namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and
abstracts of the examined documents. The representation of the results allows recognizing several significant clusters
and network relationships. Moreover, that literature review enables to identify two well-established research strands.
The first involves the relationship between energy prices and the profitability of efficiency-related investments. The
second research branch points at the pivotal role played by the discount rate when evaluating the investments in
energy-efficient measures.
© 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (
https://creativecommons.org/licenses/by-nc-nd/4.0/
)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,
Environment and Sustainability, TMREES18.
Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate
* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it
ScienceDirect
Energy Procedia 00 (2018) 000–000www.elsevier.com/locate/procedia
1876-6102 © 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18.
Technologies and Materials for Renewable Energy, Environment and Sustainability, TMREES18,
19–21 September 2018, Athens, Greece
Economic parameters in the evaluation studies focusing on
building energy efficiency: a review of the underlying
rationale, data sources, and assumptions
Sergio Copiello
a*
aIUAV University of Venice, Dorsoduro 2206, 30123 Venice, Italy
Abstract
A growing literature has highlighted the variables and parameters that most affect the technical feasibility and the
economic viability of the measures meant to improve building energy efficiency. This paper discusses the results of a
literature review, which focuses on the studies that deal with three economic parameters: the price to be paid for the
energy supply, the energy inflation rate, and the discount rate used to convert future cash flows to a present value,
namely, an upfront lump-sum equivalent. A specific co-occurrence analysis of terms is performed on the titles and
abstracts of the examined documents. The representation of the results allows recognizing several significant clusters
and network relationships. Moreover, that literature review enables to identify two well-established research strands.
The first involves the relationship between energy prices and the profitability of efficiency-related investments. The
second research branch points at the pivotal role played by the discount rate when evaluating the investments in
energy-efficient measures.
© 2018 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (
https://creativecommons.org/licenses/by-nc-nd/4.0/
)
Selection and peer-review under responsibility of the scientific committee of Technologies and Materials for Renewable Energy,
Environment and Sustainability, TMREES18.
Keywords: Building energy efficiency; Energy price; Inflation rate; Discount rate
* Corresponding author. Tel.: +39 041 257 1387; fax: +39 041 257 2424. E-mail address: copiello@iuav.it
2 Sergio Copiello / Energy Procedia 00 (2018) 000–000
1. Introduction
The issue of building energy efficiency has gained interest during the last years and, more broadly, over a time
span of four decades or so [
1] (Fig. 1
). Energy efficiency is a prominent topic on the agenda due to the need of taking
fuel consumptions under control and reducing their environmental impact. Under this framework, the construction
sector plays a pivotal role because buildings largely contribute to primary energy demand and consumption, as well
as to greenhouse gas emissions [
2-4]. Concerning the evaluation of the measures aiming at improving building energy
efficiency, a growing literature is available. The results of several field studies, although sometimes conflicting, have
the merit of having highlighted the variables and parameters that most affect the technical feasibility and the economic
viability of those measures. As far as the latter is concerned, a summary list of the most influential parameters should
include, at least, the following items [
1,5]: contingent and long-term geo-climatic conditions [6,7]; building type and
physical characteristics of the constructions [
8,9]; consumers’ preferences and occupants’ behavior [10-13]; prices of
energy supply and their changes over time [
14-16]; investment costs to be incurred and the corresponding expected
return and payback time [
17-19].
Fig. 1. Growing interest for building energy efficiency (source: Google Ngram Viewer).
This paper aims to present the results of a systematic literature review, with regard to the studies that use economic
parameters to assess the feasibility of energy efficiency measure in the building industry. The literature review
purposely focuses on the following three economic parameters: the price to be paid for the energy supply; the inflation
rate, especially as far as energy sources are concerned; the discount rate used to convert future values to present values,
so to calculate the upfront lump-sum equivalent of the expected cash flows.
The structure of this paper is as follows. The next section describes the source used to gather information and the
method followed to identify the relevant literature. The subsequent paragraph provides an overview of the results,
with specific reference to these issues: topics addressed in the studies, data sources, and estimated values or
assumptions as far as the economic parameters are concerned. A further part of the text is devoted to identify and
discuss two main, well-established research strands: the role played by energy prices in techno-economic evaluations
is the former, the prominence of the discount rate in the same evaluations is the latter. Finally, the last section draws
the conclusions.
2. Method
The literature review discussed in this study is based on bibliographic research, which has been performed using
the indexing and abstracting database Scopus, provided by Elsevier. Although some limitations and other issues are
known to affect the selected source [
20-23], it has been chosen due to its wider coverage in comparison to others such
that constitute the focus of this study - namely, energy price, energy inflation rate, and discount rate - the search string
used here is as follows:
( ALL ( “Building energy efficiency” ) AND TITLE-ABS-KEY ( “Energy price” ) OR TITLE-ABS-KEY (
“Inflation rate” ) OR TITLE-ABS-KEY ( “Discount rate” ) ).
In other words, a general key expression (“building energy efficiency”) is adopted to define the boundaries of the
analysis. That key is used to search all the abstracting database fields. In addition, three specific expressions (“energy
price”, “inflation rate”, and “discount rate”) are adopted to refine the search within titles, abstracts, and keywords.
The search returns a result of 65 published items. That number does not reflect the whole amount of studies that,
somehow, make use of the three analyzed parameters. Indeed, several other indexed documents base their analysis on
economic parameters without explicitly reporting them in the abstract or among the keywords. As a case in point, let
us consider that searching for the three key expressions (“energy price”, “inflation rate”, and “discount rate”) in all
the abstracting database fields - without limiting the search to titles, abstracts, and keywords - would produce 188
results. However, I take into account the 65 results of the search string mentioned above relying on the assumption
that mentioning an economic parameter in the abstract or among the keywords reveals that it takes on high significance
in the research work and the related publication.
It deserves mentioning a partial overlap of the results (
Fig. 2
). Although most of the analyzed studies deal only
with the parameter of the energy price or, in a subordinate position, exclusively with the discount rate, a certain number
of publications consider two parameters (i.e., the energy supply cost and the discount rate, or the energy inflation rate
and, again, the discount rate). Other few studies present empirical applications, if not even theoretical reflections,
which involve all the three parameters considered here.
Fig. 2. Summary of the bibliographic search in Scopus.
The items are characterized by a publication window of about two decades, from 1996 to 2018. However, only two
articles date back to the late nineties, while all the other documents have been published after the year 2007. What is
more, nearly 70% of the documents have been authored during the last five years. Concerning the publication venue,
the results are mostly journal articles (72%) and conference papers (23%), while only three (5%) are book chapters.
As far as the publication outlets are concerned, the journal Energy and Buildings hosts nine articles, eight other papers
have been published in Energy Policy, and five each in Energy and Journal of Cleaner Production.
3. Summary of the results
Tables 1 to 4
summarize the results (in chronological order) by reporting, for each study, the publication venue,
the economic parameter(s) considered, and the synthetic description of the topic. Besides, the number of citations (as
of April 2018) is meant to act as a proxy of the attention gained, although a low number of citations is likely to
characterize the studies published in the last couple of years. In absolute terms, the most cited study is that authored
by Newell, Jaffe, and Stavins (test of the Hicks’s induced innovation hypothesis on energy-using consumer durables),
published in 1999 in The Quarterly Journal of Economics [
28]. Other highly-cited documents are those by Zhao, Li,
and Ma (decomposition analysis of urban energy consumptions in China) and by Kumbaroğlu and Madlener
(evaluation of optimal retrofit investment options using Monte Carlo simulation), both published in 2012 [
37,38]. Out
of the 65 analyzed studies, nine are not included in the tables due to their limited relevance, namely, the fact that they
only incidentally deal with at least one of the economic parameters which this study focuses on.
Table 1. Summary of the results (first part). Economic parameter Year First author and
reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 1996 Levine, M.D.
[27] ja x Gap between energy prices and the full costs of energy production due to subsidies, which disincentive investments in energy efficiency
7 1999 Newell, R.G.
[28] ja x The relationship between product innovation and energy price in the field of energy-using consumer durables
377 2008 Scott, M.J. [29] ja x Net savings of the US building energy efficiency
programs considering UN IPCC warming scenarios (reduced need for heating and increase in space cooling demand)
12
2009 Cao, J. [30] ja x Influence of the energy price on the economic viability of a retrofit measure, showing that contradictions affect China’s energy price system
9 2009 Wu, Y. [31] cp x Energy prices are among the parameters to consider for
the building energy management to be effective and efficient
2 2010 Parfomak, P.W.
[32] bc x Policies need to address the energy price risks: uncertainty about future energy prices hinders the assumption of investment decisions about building efficiency
0
2010 Zwettler, G.
[33] cp x Energy costs are among the parameter considered in an optimization software meant to assist the design of energy efficient buildings
2 2011 Jeong, J. [34] ja x Heating energy usage patterns in the light of the
substitute/complementary relationship between gas and electricity and according to energy price and household characteristics
13
2011 Ouyang, J. [14] ja x x x Life cycle cost analysis on the upgrade of aging residential buildings in China, it is shown that growing energy prices and subsidies do not lead to a satisfactory economic viability
19
2011 Parfomak, P.W.
[35] bc x [see above the item 2010, Parfomak, P.W.] 0
2012 Haney, A.B.
[36] bc x International comparisons of demand-side management strategies and policies to improve energy efficiency, and their relationships with energy prices
6 2012 Zhao, X. [37] ja x Decomposition of China’s residential energy use,
showing that consumptions are shifting towards a more energy-intensive model and price reforms contribute to energy savings
83
that constitute the focus of this study - namely, energy price, energy inflation rate, and discount rate - the search string
used here is as follows:
( ALL ( “Building energy efficiency” ) AND TITLE-ABS-KEY ( “Energy price” ) OR TITLE-ABS-KEY (
“Inflation rate” ) OR TITLE-ABS-KEY ( “Discount rate” ) ).
In other words, a general key expression (“building energy efficiency”) is adopted to define the boundaries of the
analysis. That key is used to search all the abstracting database fields. In addition, three specific expressions (“energy
price”, “inflation rate”, and “discount rate”) are adopted to refine the search within titles, abstracts, and keywords.
The search returns a result of 65 published items. That number does not reflect the whole amount of studies that,
somehow, make use of the three analyzed parameters. Indeed, several other indexed documents base their analysis on
economic parameters without explicitly reporting them in the abstract or among the keywords. As a case in point, let
us consider that searching for the three key expressions (“energy price”, “inflation rate”, and “discount rate”) in all
the abstracting database fields - without limiting the search to titles, abstracts, and keywords - would produce 188
results. However, I take into account the 65 results of the search string mentioned above relying on the assumption
that mentioning an economic parameter in the abstract or among the keywords reveals that it takes on high significance
in the research work and the related publication.
It deserves mentioning a partial overlap of the results (
Fig. 2
). Although most of the analyzed studies deal only
with the parameter of the energy price or, in a subordinate position, exclusively with the discount rate, a certain number
of publications consider two parameters (i.e., the energy supply cost and the discount rate, or the energy inflation rate
and, again, the discount rate). Other few studies present empirical applications, if not even theoretical reflections,
which involve all the three parameters considered here.
Fig. 2. Summary of the bibliographic search in Scopus.
The items are characterized by a publication window of about two decades, from 1996 to 2018. However, only two
articles date back to the late nineties, while all the other documents have been published after the year 2007. What is
more, nearly 70% of the documents have been authored during the last five years. Concerning the publication venue,
the results are mostly journal articles (72%) and conference papers (23%), while only three (5%) are book chapters.
As far as the publication outlets are concerned, the journal Energy and Buildings hosts nine articles, eight other papers
have been published in Energy Policy, and five each in Energy and Journal of Cleaner Production.
3. Summary of the results
Tables 1 to 4
summarize the results (in chronological order) by reporting, for each study, the publication venue,
the economic parameter(s) considered, and the synthetic description of the topic. Besides, the number of citations (as
of April 2018) is meant to act as a proxy of the attention gained, although a low number of citations is likely to
characterize the studies published in the last couple of years. In absolute terms, the most cited study is that authored
by Newell, Jaffe, and Stavins (test of the Hicks’s induced innovation hypothesis on energy-using consumer durables),
published in 1999 in The Quarterly Journal of Economics [
28]. Other highly-cited documents are those by Zhao, Li,
and Ma (decomposition analysis of urban energy consumptions in China) and by Kumbaroğlu and Madlener
(evaluation of optimal retrofit investment options using Monte Carlo simulation), both published in 2012 [
37,38]. Out
of the 65 analyzed studies, nine are not included in the tables due to their limited relevance, namely, the fact that they
only incidentally deal with at least one of the economic parameters which this study focuses on.
Table 1. Summary of the results (first part). Economic parameter Year First author and
reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 1996 Levine, M.D.
[27] ja x Gap between energy prices and the full costs of energy production due to subsidies, which disincentive investments in energy efficiency
7 1999 Newell, R.G.
[28] ja x The relationship between product innovation and energy price in the field of energy-using consumer durables
377 2008 Scott, M.J. [29] ja x Net savings of the US building energy efficiency
programs considering UN IPCC warming scenarios (reduced need for heating and increase in space cooling demand)
12
2009 Cao, J. [30] ja x Influence of the energy price on the economic viability of a retrofit measure, showing that contradictions affect China’s energy price system
9 2009 Wu, Y. [31] cp x Energy prices are among the parameters to consider for
the building energy management to be effective and efficient
2 2010 Parfomak, P.W.
[32] bc x Policies need to address the energy price risks: uncertainty about future energy prices hinders the assumption of investment decisions about building efficiency
0
2010 Zwettler, G.
[33] cp x Energy costs are among the parameter considered in an optimization software meant to assist the design of energy efficient buildings
2 2011 Jeong, J. [34] ja x Heating energy usage patterns in the light of the
substitute/complementary relationship between gas and electricity and according to energy price and household characteristics
13
2011 Ouyang, J. [14] ja x x x Life cycle cost analysis on the upgrade of aging residential buildings in China, it is shown that growing energy prices and subsidies do not lead to a satisfactory economic viability
19
2011 Parfomak, P.W.
[35] bc x [see above the item 2010, Parfomak, P.W.] 0
2012 Haney, A.B.
[36] bc x International comparisons of demand-side management strategies and policies to improve energy efficiency, and their relationships with energy prices
6 2012 Zhao, X. [37] ja x Decomposition of China’s residential energy use,
showing that consumptions are shifting towards a more energy-intensive model and price reforms contribute to energy savings
83
Table 2. Summary of the results (second part). Economic parameter Year First author and
reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 2012 Kumbaroglu, G.
[38] ja x x Case study of building retrofit addressing uncertainty in energy prices through Monte Carlo simulation, showing that their changes significantly affect the profitability of the investments
66
2013 Cajias, M. [39] ja x Financial performance of German housing: energy efficiency affects tenant decisions (0.76 Eur/m2 higher rent) and the performance of investor portfolios (up to 3.15% higher return)
30
2013 Cox, M. [40] ja x Revision of the projected investments in energy-efficient equipment and related energy consumptions in the US according to different levels of the discount rate
16
2013 Egging, R. [41] ja x Discussion on the drivers and uncertainties in the recent and future energy market trends, especially as far as energy prices are concerned
6 2014 Wu, W. [42] ja x Techno-economic analysis of a combined heat supply
system, linking heating period, energy price, and payback period
11 2014 Deng, Q. [43] ja x Analysis and discussion of a simulation-based decision
model to design contract period in the field of Energy Performance Contracting
17 2014 Yan, X. [44] ja x x Techno-economic analysis of energy storage systems:
the sensitivity analysis reveals that the discount rate has the largest influence on the viability of the analyzed systems
20
2014 Qian, D. [45] ja x x Development of a revenue-sharing bargaining model within Energy Performance Contracting and analysis of the impacts of energy prices and risk-adjusted discount rates
16
2014 Bonakdar, F.
[46] ja x x Analysis of the cost-optimum level of renovation in a multi-story residential building according to different discount rates and energy prices
19 2014 Adika, C.O.
[47] ja x Approach to the development of an automated appliance scheduling system for household energy management including expected energy prices
81 2015 Guo, L. [48] cp x Optimization methodology to minimize the energy cost
under energy price uncertainty: random price changes with a known underlying distribution
2 2015 Wu, L. [49] ja x Environmental, economic analysis of a water supply
facility incorporating climate externalities: a higher discount rate counteracts the effectiveness of the carbon cost factor
8
2015 Lin, B. [50] ja x Analysis of building energy consumptions and building energy efficiency in light of urbanization process and energy price trends
32 2015 Deng, Q. [51] ja x x x Energy cost savings model, meant to improve Energy
Performance Contracting, which accounts for energy price fluctuation using Monte Carlo simulation
14 2015 Deng, Q. [52] ja x Simulation-based model to maximize the facility
owner’s profit and satisfy the ESCo’s expected rate of return
7 (1) ja: journal article; cp: conference paper; bc: book chapter.
Table 3. Summary of the results (third part). Economic parameter Year First author Venue
(1) Energy price Inflation rate Discount rate Topic Citations 2015 Lin, B. [53] ja x Analysis of the substitution relationship between each
input factor including energy in China’s food industry, showing that a direct rebound effect partially offsets energy savings
4
2016 Lin, B. [54] ja x Analysis of energy rebound effect in China’s light industry considering the effects of energy prices on energy consumptions
11 2016 Roshchanka, V.
[55] ja x Feedbacks about the use of Energy Performance Contracts and the development of the ESCos’ business model in the Russian Federation
4 2016 Liu, X. [56] ja x Model meant to determine the optimal value of the
discount rate that enables to take emissions under controls in building procurement contracts
0 2016 Ameer, B. [57] ja x x Impact of heavily subsidized energy prices for the
residential building sector in Kuwait: need to increase the electricity price to improve energy savings and efficiency in building
8
2016 Good, N. [58] ja x Techno-economic framework for the assessment of business cases of low carbon technologies, with a focus on multiple energy systems and vectors
19 2016 Krarti, M. [59] ja x x Analysis of the cost-effectiveness potential of net-zero
energy residential buildings in the Middle East and North Africa region, which is found to strongly depends on energy prices
11
2016 Brandão de Vasconcelos, A. [60]
ja x Cost-optimal analysis of several refurbishment
scenarios accounting for different discount rate using sensitivity analysis
3 2016 Liu, H. [61] ja x Analysis of the impacts of technological advancement
on energy consumption in China’s building industry in light of the direct rebound effect
6 2016 He, L. [62] ja x Analysis to test the hypothesis that the relative energy
price and not the absolute one is the most important to explain energy consumptions
1 2017 Miezis, M. [63] cp x Algorithm for model predictive control (MPC) in
multi-family buildings, including energy prices as constraints, with application to a case study in Latvia
3 2017 Copiello, S. [1] ja x Review of the paradoxes affecting the research topics
focusing on building energy efficiency, one of which relates to the relationship between investments and energy prices
14
2017 Khabdullin, A.
[64] cp x Analysis of the possible use of electricity as a source for district heating systems considering electricity price in comparison with heat energy price
0 2017 Krarti, M. [65] ja x x Evaluation of economic and environmental impacts of
energy efficiency programs for new and existing buildings in Saudi Arabia under conditions of highly subsidized energy prices
1
2017 Weeber, M.
[66] cp x Overview and discussion of opportunities, risks, and trends associated with the topic of energy flexibility in a context of fluctuating energy prices
0 2017 Simona, P.L.
[67] cp x Study on increasing energy efficiency in collective residential buildings by acting on their thermal insulation
0 (1) ja: journal article; cp: conference paper; bc: book chapter.
Table 2. Summary of the results (second part). Economic parameter Year First author and
reference Venue (1) Energy price Inflation rate Discount rate Topic Citations 2012 Kumbaroglu, G.
[38] ja x x Case study of building retrofit addressing uncertainty in energy prices through Monte Carlo simulation, showing that their changes significantly affect the profitability of the investments
66
2013 Cajias, M. [39] ja x Financial performance of German housing: energy efficiency affects tenant decisions (0.76 Eur/m2 higher rent) and the performance of investor portfolios (up to 3.15% higher return)
30
2013 Cox, M. [40] ja x Revision of the projected investments in energy-efficient equipment and related energy consumptions in the US according to different levels of the discount rate
16
2013 Egging, R. [41] ja x Discussion on the drivers and uncertainties in the recent and future energy market trends, especially as far as energy prices are concerned
6 2014 Wu, W. [42] ja x Techno-economic analysis of a combined heat supply
system, linking heating period, energy price, and payback period
11 2014 Deng, Q. [43] ja x Analysis and discussion of a simulation-based decision
model to design contract period in the field of Energy Performance Contracting
17 2014 Yan, X. [44] ja x x Techno-economic analysis of energy storage systems:
the sensitivity analysis reveals that the discount rate has the largest influence on the viability of the analyzed systems
20
2014 Qian, D. [45] ja x x Development of a revenue-sharing bargaining model within Energy Performance Contracting and analysis of the impacts of energy prices and risk-adjusted discount rates
16
2014 Bonakdar, F.
[46] ja x x Analysis of the cost-optimum level of renovation in a multi-story residential building according to different discount rates and energy prices
19 2014 Adika, C.O.
[47] ja x Approach to the development of an automated appliance scheduling system for household energy management including expected energy prices
81 2015 Guo, L. [48] cp x Optimization methodology to minimize the energy cost
under energy price uncertainty: random price changes with a known underlying distribution
2 2015 Wu, L. [49] ja x Environmental, economic analysis of a water supply
facility incorporating climate externalities: a higher discount rate counteracts the effectiveness of the carbon cost factor
8
2015 Lin, B. [50] ja x Analysis of building energy consumptions and building energy efficiency in light of urbanization process and energy price trends
32 2015 Deng, Q. [51] ja x x x Energy cost savings model, meant to improve Energy
Performance Contracting, which accounts for energy price fluctuation using Monte Carlo simulation
14 2015 Deng, Q. [52] ja x Simulation-based model to maximize the facility
owner’s profit and satisfy the ESCo’s expected rate of return
7 (1) ja: journal article; cp: conference paper; bc: book chapter.
Table 3. Summary of the results (third part). Economic parameter Year First author Venue
(1) Energy price Inflation rate Discount rate Topic Citations 2015 Lin, B. [53] ja x Analysis of the substitution relationship between each
input factor including energy in China’s food industry, showing that a direct rebound effect partially offsets energy savings
4
2016 Lin, B. [54] ja x Analysis of energy rebound effect in China’s light industry considering the effects of energy prices on energy consumptions
11 2016 Roshchanka, V.
[55] ja x Feedbacks about the use of Energy Performance Contracts and the development of the ESCos’ business model in the Russian Federation
4 2016 Liu, X. [56] ja x Model meant to determine the optimal value of the
discount rate that enables to take emissions under controls in building procurement contracts
0 2016 Ameer, B. [57] ja x x Impact of heavily subsidized energy prices for the
residential building sector in Kuwait: need to increase the electricity price to improve energy savings and efficiency in building
8
2016 Good, N. [58] ja x Techno-economic framework for the assessment of business cases of low carbon technologies, with a focus on multiple energy systems and vectors
19 2016 Krarti, M. [59] ja x x Analysis of the cost-effectiveness potential of net-zero
energy residential buildings in the Middle East and North Africa region, which is found to strongly depends on energy prices
11
2016 Brandão de Vasconcelos, A. [60]
ja x Cost-optimal analysis of several refurbishment scenarios accounting for different discount rate using sensitivity analysis
3 2016 Liu, H. [61] ja x Analysis of the impacts of technological advancement
on energy consumption in China’s building industry in light of the direct rebound effect
6 2016 He, L. [62] ja x Analysis to test the hypothesis that the relative energy
price and not the absolute one is the most important to explain energy consumptions
1 2017 Miezis, M. [63] cp x Algorithm for model predictive control (MPC) in
multi-family buildings, including energy prices as constraints, with application to a case study in Latvia
3 2017 Copiello, S. [1] ja x Review of the paradoxes affecting the research topics
focusing on building energy efficiency, one of which relates to the relationship between investments and energy prices
14
2017 Khabdullin, A.
[64] cp x Analysis of the possible use of electricity as a source for district heating systems considering electricity price in comparison with heat energy price
0 2017 Krarti, M. [65] ja x x Evaluation of economic and environmental impacts of
energy efficiency programs for new and existing buildings in Saudi Arabia under conditions of highly subsidized energy prices
1
2017 Weeber, M.
[66] cp x Overview and discussion of opportunities, risks, and trends associated with the topic of energy flexibility in a context of fluctuating energy prices
0 2017 Simona, P.L.
[67] cp x Study on increasing energy efficiency in collective residential buildings by acting on their thermal insulation
0 (1) ja: journal article; cp: conference paper; bc: book chapter.
Table 4. Summary of the results (fourth part). Economic parameter Year First author Venue
(1) Energy price Inflation rate Discount rate Topic Citations 2017 Di Giuseppe, E.
[68] cp x x Characterization of the stochastic inputs of a probabilistic Life Cycle Cost Analysis: inflation and discount rate are among the most influential parameters
0 2017 Dodoo, A. [69] ja x x Renovation of a multi-story residential building: real
discount rate and energy price increase have a significant impact on the cost-effectiveness and profitability of the measures
2
2017 Copiello, S. [5] ja x x x Life-Cycle Cost and Monte Carlo simulation: the discount rate is a prominent source of uncertainty and affects the results four times as much as the energy price
2
2017 Das, P. [70] ja x x Case-study retrofitting of Swedish attics: increments in energy costs and discount rates can impact the optimal design option
0 2017 Cui, T. [71] ja x Co-scheduling problem of Heating, Ventilation and Air
Conditioning (HVAC) and Hybrid Electrical Energy Storage (HEES) systems under dynamic energy prices
0 2017 Copiello, S. [4] ja x Analysis of building energy consumption: the role
played by both energy price and household income is worth attention with respect to the direct rebound effect
0
2017 Li, M.-J. [72] ja x Cointegration analysis of the relationship between energy consumption and its underlying explanations including energy price, economic development, and industrial structure
0
2017 Balin, A. [73] ja x Fuzzy multi-criteria decision making (MCDM) method to determine the best renewable energy alternatives for Turkey
4 2017 Zhang, Y. [74] ja x x Design of an integrated system including thermal
energy storage and building cooling, heating and power: its operation strategy highly depends on natural gas and electricity prices
1
2017 Lei, Y. [75] cp x Assessment of three residential space heating options: ground source heat pump, air source heat pump, and wall-hung gas boiler
0 2018 Dodoo, A. [76] ja x x Cost-effectiveness of the energy renovation measures
for a district heated building: the economic viability is sensitive to discount rates and energy price increase
0 2018 Agliardi, E. [77] ja x x x Techno-economic evaluation method for deep
renovation of buildings based on the real option theory, modeling energy price uncertainty through a mean-reverting stochastic process
0
2018 Liu, Y. [78] ja x x x Case study of cost-benefit analysis for energy retrofit of existing buildings: energy price is found to be the most sensitive factor
1 (1) ja: journal article; cp: conference paper; bc: book chapter.
The topics vary in a well-defined range. Several papers directly tackle problems related to energy prices and energy
supply costs. Earlier publications mostly address issues pertaining to energy policies and energy-related incentive
programs [
27,29,32,35-37], while recent documents, especially during the last decade, are more prone to focus their
attention on case studies, providing techno-economic analyses of investments in specific energy efficiency measures
and solutions [
14,38,42,44,46,58,60,67,69,70,75-78]. As far as those investments are concerned, the issue of
uncertainty is addressed [
5,41,48,68], and decision support systems are proposed [43,52,73]. The relationship between
the discount rate and the environmental aspects, notably greenhouse gas emissions, represents a kind of niche topic
among the analyzed studies [
49,56].
Building on a corpus of text data, namely the titles and abstracts of the examined publications, a co-occurrence
analysis of terms has been performed using the software VOSviewer [
79,80]. Recurring terms have been analyzed
according to a binary counting method; namely, only their presence does matter, while the overall number of their
occurrences is not considered. The minimum number of occurrences has been set to five, finding 69 terms that meet
the threshold. The resulting network representation (
Fig. 3
) considers the 60% most relevant items, hence 41 terms.
Fig. 3. Network representation of the co-occurrence analysis of terms.
Recognizing at least three significant fuzzy clusters of recurrent terms or expressions is possible. The first one (red
dots in
Fig. 3
) is arranged around the terms “development” (15 occurrences), “demand”, and “increase” (12
occurrences each). It is worthwhile to notice that the same cluster includes several other relevant terms, which
contribute to define its shape and boundaries. The focus is mainly on “energy efficiency improvement” and “energy
conservation” (six and seven occurrences, respectively), in buildings and specifically in the “residential sector”, with
a remarkable interest in “electricity” as an energy source and its price. The environmental concerns are subsumed
under to topic of “climate change”. The second cluster (blue dots in
Fig. 3
) features a core set made of few,
interconnected terms or expressions. The main term is “investment” (14 occurrences), which is also near to terms such
as “goal” and “decision”. Finally, the most representative terms and expressions of the third cluster (green dots in
Fig.
3
) are “energy saving” (16 occurrences) and “uncertainty” (13). The first item is near to “case study” analyses, wherein
the “discount rate” parameter (12 occurrences) is significant. The second item recalls other terms fitting the cluster,
such as “evaluation”, “sensitivity analysis”, and “simulation”. Within the cluster, a kind of subset refers to the “energy
service company”, often identified with the acronym “esco”, under the framework of “epc” which stands for energy
performance contracting.
Turning to the data sources, as well as to the estimates and the assumptions about the economic parameters, a
summary of empirical evidence is reported in
Table 5
. Concerning the historical series of energy prices and their
change rates, commonly used data source are IEA (International Energy Agency) and EIA (Energy Information
Administration).
Table 4. Summary of the results (fourth part). Economic parameter Year First author Venue
(1) Energy price Inflation rate Discount rate Topic Citations 2017 Di Giuseppe, E.
[68] cp x x Characterization of the stochastic inputs of a probabilistic Life Cycle Cost Analysis: inflation and discount rate are among the most influential parameters
0 2017 Dodoo, A. [69] ja x x Renovation of a multi-story residential building: real
discount rate and energy price increase have a significant impact on the cost-effectiveness and profitability of the measures
2
2017 Copiello, S. [5] ja x x x Life-Cycle Cost and Monte Carlo simulation: the discount rate is a prominent source of uncertainty and affects the results four times as much as the energy price
2
2017 Das, P. [70] ja x x Case-study retrofitting of Swedish attics: increments in energy costs and discount rates can impact the optimal design option
0 2017 Cui, T. [71] ja x Co-scheduling problem of Heating, Ventilation and Air
Conditioning (HVAC) and Hybrid Electrical Energy Storage (HEES) systems under dynamic energy prices
0 2017 Copiello, S. [4] ja x Analysis of building energy consumption: the role
played by both energy price and household income is worth attention with respect to the direct rebound effect
0
2017 Li, M.-J. [72] ja x Cointegration analysis of the relationship between energy consumption and its underlying explanations including energy price, economic development, and industrial structure
0
2017 Balin, A. [73] ja x Fuzzy multi-criteria decision making (MCDM) method to determine the best renewable energy alternatives for Turkey
4 2017 Zhang, Y. [74] ja x x Design of an integrated system including thermal
energy storage and building cooling, heating and power: its operation strategy highly depends on natural gas and electricity prices
1
2017 Lei, Y. [75] cp x Assessment of three residential space heating options: ground source heat pump, air source heat pump, and wall-hung gas boiler
0 2018 Dodoo, A. [76] ja x x Cost-effectiveness of the energy renovation measures
for a district heated building: the economic viability is sensitive to discount rates and energy price increase
0 2018 Agliardi, E. [77] ja x x x Techno-economic evaluation method for deep
renovation of buildings based on the real option theory, modeling energy price uncertainty through a mean-reverting stochastic process
0
2018 Liu, Y. [78] ja x x x Case study of cost-benefit analysis for energy retrofit of existing buildings: energy price is found to be the most sensitive factor
1 (1) ja: journal article; cp: conference paper; bc: book chapter.
The topics vary in a well-defined range. Several papers directly tackle problems related to energy prices and energy
supply costs. Earlier publications mostly address issues pertaining to energy policies and energy-related incentive
programs [
27,29,32,35-37], while recent documents, especially during the last decade, are more prone to focus their
attention on case studies, providing techno-economic analyses of investments in specific energy efficiency measures
and solutions [
14,38,42,44,46,58,60,67,69,70,75-78]. As far as those investments are concerned, the issue of
uncertainty is addressed [
5,41,48,68], and decision support systems are proposed [43,52,73]. The relationship between
the discount rate and the environmental aspects, notably greenhouse gas emissions, represents a kind of niche topic
among the analyzed studies [
49,56].
Building on a corpus of text data, namely the titles and abstracts of the examined publications, a co-occurrence
analysis of terms has been performed using the software VOSviewer [
79,80]. Recurring terms have been analyzed
according to a binary counting method; namely, only their presence does matter, while the overall number of their
occurrences is not considered. The minimum number of occurrences has been set to five, finding 69 terms that meet
the threshold. The resulting network representation (
Fig. 3
) considers the 60% most relevant items, hence 41 terms.
Fig. 3. Network representation of the co-occurrence analysis of terms.
Recognizing at least three significant fuzzy clusters of recurrent terms or expressions is possible. The first one (red
dots in
Fig. 3
) is arranged around the terms “development” (15 occurrences), “demand”, and “increase” (12
occurrences each). It is worthwhile to notice that the same cluster includes several other relevant terms, which
contribute to define its shape and boundaries. The focus is mainly on “energy efficiency improvement” and “energy
conservation” (six and seven occurrences, respectively), in buildings and specifically in the “residential sector”, with
a remarkable interest in “electricity” as an energy source and its price. The environmental concerns are subsumed
under to topic of “climate change”. The second cluster (blue dots in
Fig. 3
) features a core set made of few,
interconnected terms or expressions. The main term is “investment” (14 occurrences), which is also near to terms such
as “goal” and “decision”. Finally, the most representative terms and expressions of the third cluster (green dots in
Fig.
3
) are “energy saving” (16 occurrences) and “uncertainty” (13). The first item is near to “case study” analyses, wherein
the “discount rate” parameter (12 occurrences) is significant. The second item recalls other terms fitting the cluster,
such as “evaluation”, “sensitivity analysis”, and “simulation”. Within the cluster, a kind of subset refers to the “energy
service company”, often identified with the acronym “esco”, under the framework of “epc” which stands for energy
performance contracting.
Turning to the data sources, as well as to the estimates and the assumptions about the economic parameters, a
summary of empirical evidence is reported in
Table 5
. Concerning the historical series of energy prices and their
change rates, commonly used data source are IEA (International Energy Agency) and EIA (Energy Information
Administration).
Table 5. Summary of the results: sources, data, and assumptions. Year First author
and reference Sources Data and assumptions
2011 Ouyang, J. [14] Central Bank; National Bureau of Statistics;
Government data Inflation rate: 3%; Increase rate of electricity price: 2%; Discount rate: 6% 2012 Kumbaroglu,
G. [38] Historical time series (1999–2010) of real energy prices and price change rates Discount rate: 4.22% (estimates within the range 2.17-7.87%) 2013 Cajias, M. [39] German Investment Property Databank;
Federal Statistical Office
2013 Cox, M. [40] Energy Information Administration 2013 Egging, R. [41] Eurostat; Int. Energy Agency; Energy Inf.
Administration
2014 Deng, Q. [43] US Department of Energy; Energy
Information Administration
2014 Yan, X. [44] Central Bank; Government data; other
literature Discount rate: 9%
2014 Qian, D. [45] Yearbooks; other literature 2014 Bonakdar, F.
[46] National Energy Agency; other literature Energy price increase: 2%; Discount rate: 1%, 3%, 5%
2015 Wu, L. [49] Government data Discount rate: 6%
2015 Lin, B. [50] National Bureau of Statistics
2015 Deng, Q. [51] Government data; other agencies Energy price: $26.03/MMBTU; Discount rate (Expected return): 10%
2015 Deng, Q. [52] US Department of Energy
2015 Lin, B. [53] Yearbooks 2016 Lin, B. [54] Yearbooks 2016 Roshchanka,
V. [55] International Energy Agency; Government data Energy price: $0.087 per kWh (residential consumers) 2016 Ameer, B. [57] Government data; other literature Energy price: $0.007/kWh (residential
consumers); Discount rate: 5% 2016 Krarti, M. [59] Other literature Energy prices: 0.094 $/kWh and 0.162
$/m3; Discount rate: 5% 2016 Brandão de
Vasconcelos, A. [60]
Government data; other literature Discount rate: 3% (2-4% and 6%), 6% (5-7% and 10%)
2016 Liu, H. [61] Yearbooks
2017 Krarti, M. [65] Energy price: $0.05/kWh (residential
customer); Discount rate: 3% 2017 Di Giuseppe,
E. [68] Central Bank; Energy Inf. Administration; US Dept. of Energy Inflation rate: 1.9%; Interest rate: 4.09%
2017 Dodoo, A. [69] Energy price increase: 1%, 2%, 3%;
Discount rate: 1%, 3%, 5%
2017 Copiello, S. [5] Other literature Energy price 0.05-0.146€/kWh; Infl.: 0-4.5%; Discount rate: 0-15%
2017 Zhang, Y. [74] Central Bank; other literature Discount rate: 10%
2018 Dodoo, A. [76] Other literature Energy price increase: 1%, 2%, 3%; Discount rate: 1%, 3%, 5% 2018 Agliardi, E.
[77] Company data; other literature Energy price: 0,95€/m3; 0,18€/kWh; Inf: 8%; Interest rate: 3%
2018 Liu, Y. [78] Energy price increase: 5%, 10%, 15%,
20%